Com中的Homography,inliers / Emgu CV / SURF

时间:2011-01-09 16:25:19

标签: c# surf computer-vision

如何使用单应性或C#中的其他方法获取匹配的kyepoints的内部/异常值?

我正在研究http://www.emgu.com/wiki/index.php/SURF_feature_detector_in_CSharp上提供的SURF示例。

我得到了匹配功能。代码使用HomographyMatrix(单应性)。我想分离内点和异常值。

在C ++中:

bgroup({findFundamentalMat})

int cvFindFundamentalMat(const CvMat* points1, const CvMat* points2, 
    CvMat* fundamentalMatrix, int method=CV_FM_RANSAC, double param1=1., 
    double param2=0.99, CvMat* status=NULL)

返回内部函数。我是否也可以在C#中看到类似的代码。

我再次需要异常值/内点分离。

3 个答案:

答案 0 :(得分:7)

如果你想要内部/异常值分离并且你已经有了匹配,试试这个:

//**RANSAC OUTLIER REMOVAL **//
Mat status;
vector<Point2f> trainMatches;
vector<Point2f> queryMatches;
vector<DMatch> inliers; 

    for( int i = 0; i < goodmatches.size(); i++ )
    {
        //-- Get the keypoints from the good matches
        trainMatches.push_back( cv::Point2f(keypointsB[ goodmatches[i].trainIdx ].pt.x/640.0f, keypointsB[ goodmatches[i].trainIdx ].pt.y/480.0f) );
        queryMatches.push_back( cv::Point2f(keypointsA[ goodmatches[i].queryIdx ].pt.x/640.0f, keypointsA[ goodmatches[i].queryIdx ].pt.y/480.0f) );
    }   

    Mat _homography;    
    Mat h = cv::findHomography(trainMatches,queryMatches,CV_RANSAC,0.005, status);

    for(size_t i = 0; i < queryMatches.size(); i++) 
    {
        if(status.at<char>(i) != 0) 
        {
            inliers.push_back(goodmatches[i]);
        }
    }

请注意,我对点进行了标准化,因此Homography估计更加稳健。

答案 1 :(得分:6)

你的问题不是那么清楚,因为如果使用emgucv单应性计算,如果有超过10个匹配对,则使用RANSAC使用CameraCalibration.FindHomography()函数进行估算。 我正在为我的论文研究这些主题,所以我会发布一些相关的代码,这些代码应该完全回复你并且还能为其他人服务。

result = MatchingRefinement.VoteForSizeAndOrientation(result, 1.5, 20);
homography = MatchingRefinement.
    GetHomographyMatrixFromMatchedFeatures(result, 
        HomographyDirection.DIRECT, HOMOGRAPHY_METHOD.LMEDS);
inverseHomography = MatchingRefinement.GetHomographyMatrixFromMatchedFeatures(
    result, HomographyDirection.INVERSE, HOMOGRAPHY_METHOD.LMEDS);

PointF[] pts1 = new PointF[result.Length];
PointF[] pts1_t = new PointF[result.Length];
PointF[] pts2 = new PointF[result.Length];

for (int i = 0; i < result.Length; i++)
{
    pts1[i] = result[i].ObservedFeature.KeyPoint.Point;
    pts1_t[i] = result[i].ObservedFeature.KeyPoint.Point;
    pts2[i] = result[i].SimilarFeatures[0].Feature.KeyPoint.Point;
}

// Project model features according to homography
homography.ProjectPoints(pts1_t);

Image<Bgr, Byte> finalCorrespondance = inputImage.Copy();

matchedInliersFeatures = new List<MatchedImageFeature>();

for (int i1 = 0; i1 < pts1_t.Length; i1++)
{
    if (Math.Sqrt(Math.Pow(pts2[i1].X - pts1_t[i1].X, 2d) + 
        Math.Pow(pts2[i1].Y - pts1_t[i1].Y, 2d)) <4d) // Inlier
    {
        PointF p_t = pts1_t[i1];
        PointF p = pts1[i1];
        finalCorrespondance.Draw(new CircleF(p, 2f), 
            new Bgr(Color.Yellow), 2);
        finalCorrespondance.Draw(new CircleF(p_t, 2f), 
            new Bgr(Color.Black), 2);
        finalCorrespondance.Draw(new LineSegment2DF(p, p_t), 
            new Bgr(Color.Blue), 1);

        MatchedImageFeature feature = new MatchedImageFeature();
        feature.SimilarFeatures = new SimilarFeature[] { 
            result[i1].SimilarFeatures[0] 
        };
        feature.ObservedFeature = result[i1].ObservedFeature;
        matchedInliersFeatures.Add(feature);
    }
}

List<ImageFeature> inliers = new List<ImageFeature>();
foreach (MatchedImageFeature match in matchedInliersFeatures)
{
    inliers.Add(match.ObservedFeature);
    inliers.Add(match.SimilarFeatures[0].Feature);
}

答案 2 :(得分:1)

C#中cvFindFundamentalMat的签名如下所示:

int cvFindFundamentalMat(CvMat points1, CvMat points2, CvMat fundamentalMatrix, 
     CV_FM method, double param1, double param2, CvMat status);

参数默认值是在C#4.0中引入的。我假设Emgu CV还不支持.Net 4.0(如果我错了,请纠正我),因此可以提供提供默认值的重载:

int cvFindFundamentalMat(CvMat points1, CvMat points2, CvMat fundamentalMatrix)
{
    return cvFindFundamentalMat(points1, points2, fundamentalMatrix,
           CV_FM.CV_FM_RANSAC, 1.0, 0.99, null);
}

注意:正如评论者所说,很难确定你要求的是什么。在这里,我猜想你的一些问题是C#中提供的C ++代码是如何形成的。